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Robust Entangled-Photon Ghost Imaging with Compressive Sensing
This work experimentally demonstrates that the imaging quality of quantum ghost imaging (GI) with entangled photons can be significantly improved by properly handling the errors caused by the imperfection of optical devices. We also consider compressive GI to reduce the number of measurements and th...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6339165/ https://www.ncbi.nlm.nih.gov/pubmed/30621087 http://dx.doi.org/10.3390/s19010192 |
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author | Li, Jun Gao, Wenyu Qian, Jiachuan Guo, Qinghua Xi, Jiangtao Ritz, Christian H. |
author_facet | Li, Jun Gao, Wenyu Qian, Jiachuan Guo, Qinghua Xi, Jiangtao Ritz, Christian H. |
author_sort | Li, Jun |
collection | PubMed |
description | This work experimentally demonstrates that the imaging quality of quantum ghost imaging (GI) with entangled photons can be significantly improved by properly handling the errors caused by the imperfection of optical devices. We also consider compressive GI to reduce the number of measurements and thereby the data acquisition time. The image reconstruction is formulated as a sparse total least square problem which is solved with an iterative algorithm. Our experiments show that, compared with existing methods, the new method can achieve a significant performance gain in terms of mean square error and peak signal–noise ratio. |
format | Online Article Text |
id | pubmed-6339165 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-63391652019-01-23 Robust Entangled-Photon Ghost Imaging with Compressive Sensing Li, Jun Gao, Wenyu Qian, Jiachuan Guo, Qinghua Xi, Jiangtao Ritz, Christian H. Sensors (Basel) Article This work experimentally demonstrates that the imaging quality of quantum ghost imaging (GI) with entangled photons can be significantly improved by properly handling the errors caused by the imperfection of optical devices. We also consider compressive GI to reduce the number of measurements and thereby the data acquisition time. The image reconstruction is formulated as a sparse total least square problem which is solved with an iterative algorithm. Our experiments show that, compared with existing methods, the new method can achieve a significant performance gain in terms of mean square error and peak signal–noise ratio. MDPI 2019-01-07 /pmc/articles/PMC6339165/ /pubmed/30621087 http://dx.doi.org/10.3390/s19010192 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Li, Jun Gao, Wenyu Qian, Jiachuan Guo, Qinghua Xi, Jiangtao Ritz, Christian H. Robust Entangled-Photon Ghost Imaging with Compressive Sensing |
title | Robust Entangled-Photon Ghost Imaging with Compressive Sensing |
title_full | Robust Entangled-Photon Ghost Imaging with Compressive Sensing |
title_fullStr | Robust Entangled-Photon Ghost Imaging with Compressive Sensing |
title_full_unstemmed | Robust Entangled-Photon Ghost Imaging with Compressive Sensing |
title_short | Robust Entangled-Photon Ghost Imaging with Compressive Sensing |
title_sort | robust entangled-photon ghost imaging with compressive sensing |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6339165/ https://www.ncbi.nlm.nih.gov/pubmed/30621087 http://dx.doi.org/10.3390/s19010192 |
work_keys_str_mv | AT lijun robustentangledphotonghostimagingwithcompressivesensing AT gaowenyu robustentangledphotonghostimagingwithcompressivesensing AT qianjiachuan robustentangledphotonghostimagingwithcompressivesensing AT guoqinghua robustentangledphotonghostimagingwithcompressivesensing AT xijiangtao robustentangledphotonghostimagingwithcompressivesensing AT ritzchristianh robustentangledphotonghostimagingwithcompressivesensing |